In this paper, we consider the problem of cross-document co-reference (CDC). Existing approaches tend to treat CDC as an information retrieval based problem and use features such as TF-IDF cosine similarity to cluster documents and/or co-reference chains. We augmented these features with features based on biographical attributes, such as occupation, nationality, gender, etc., obtained by using ...

In some statistical process control applications, the combination of both variable and attribute quality characteristics which are correlated represents the quality of the product or the process. In such processes, identification the time of manifesting the out-of-control states can help the quality engineers to eliminate the assignable causes through proper corrective actions. In this paper, f...

Because of the complexity of decision-making environment, the uncertainty of fuzziness and the uncertainty of grey maybe coexist in the problems of multi-attribute group decision making. In this paper, we study the problems of multi-attribute group decision making with hybrid grey attribute data (the precise values, interval numbers and linguistic fuzzy variables coexist, and each attribute val...

This paper proposes a new measure for similarity between basket datasets. The new measure is calculated from support counts using a formula inspired by information entropy. Experiments on both real and synthetic datasets show the effectiveness of the measure. This paper also studies the problem of finding a mapping between categorical database attribute sets using similarity measures. A generic...

Saccadic reaction time (SRT) is more strongly slowed by target-similar than dissimilar distractors (similarity effect). The time course of this similarity effect was investigated by varying target contrast and analyzing SRT distributions. With foveal distractors, the similarity effect increased with increasing SRT, suggesting that top-down enhancement of target features increased over time. Thi...

Embedding learning (EL) and feature synthesizing (FS) are two of the popular categories fine-grained GZSL methods. EL or FS using global features cannot discriminate fine details in absence local features. On other hand, methods exploiting either neglect direct attribute guidance information. Consequently, neither method performs well. In this paper, we propose to explore attribute-supervised v...

Most similarity measures assume that each attribute for an object has a single value. However, there are many attributes that have a set or bag of values. This paper first discusses various similarity measures for single-valued attributes, group similarity measures, then proposes a unified framework for similarity measures that can cope with data sets with mixed types of attributes that may hav...

In case-based reasoning, improving the performance of the retrieval phase is still an important research issue for complex case representations and computationally expensive similarity measures. This holds particularly for the of retrieval workflows, which is a recent topic in process-oriented case-based reasoning. While most index-based retrieval methods are restricted to attribute-value repre...

DNA microarrays (gene chips), frequently used in biological and medical studies, measure the expressions of thousands of genes per sample. Using microarray data to build accurate classifiers for diseases is an important task. This paper introduces an algorithm, called Committee of Decision Trees by Attribute Behavior Diversity (CABD), to build highly accurate ensembles of decision trees for suc...